Data file: ic_t1d_onengut_allresults.csv.
immunochip-regions.txt –> chr1:113863087-114527968.ic_t1d_onengut_allresults.csv file (694 SNPs).aligned9.build37.RData to get LD matrix for these SNPs (drop 55 SNPs here which do not appear in this file –> 639 SNPs). Sigma <- ld(Xsub, Xsub, stat="R")## $Credset
## name.rs pp
## 1 rs2476601 0.8640309
## 2 rs6679677 0.1359691
##
## $Claimed
## [1] 1
##
## $Corrected
## [1] 0.8035921
##
## $nSNPs_in_region
## [1] 639
share/Projects/abc/input_files/refdatasets/datafilesD/ –> chr1:113619999-114460000 and convert the SNP names to rs IDs. Remove variants whose names cannot be matched (583 SNPs left).ic_t1d_onengut_allresults.csv file (640 SNPs).LD <- cor2(x)## $Credset
## name.rs pp
## 1 rs2476601 0.8640309
## 2 rs6679677 0.1359691
##
## $Claimed
## [1] 1
##
## $Corrected
## [1] 0.889136
##
## $nSNPs_in_region
## [1] 520
Find the SNPs which are used in both the above methods (495 the same).
Proceed as normal for both methods.
Do they both get stuck in a loop? Yes.
Build 37 Method:
Build 36 Method:
## $build37_claim
## [1] 1
##
## $build37_corr
## [1] 0.882864
##
## $build37_reqthr
## [1] 1
##
## $build37_newCS_claim
## [1] 1
##
## $build37_newCS_corr
## [1] 0.989864
##
## $build36_claim
## [1] 1
##
## $build36_corr
## [1] 0.8977281
##
## $build36_reqthr
## [1] 1
##
## $build36_newCS_claim
## [1] 1
##
## $build36_newCS_corr
## [1] 0.989864